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Proceedings Paper

Corn tassel detection based on image processing
Author(s): Wenbing Tang; Yane Zhang; Dongxing Zhang; Wei Yang; Minzan Li
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Paper Abstract

Machine vision has been widely applied in facility agriculture, and played an important role in obtaining environment information. In this paper, it is studied that application of image processing to recognize and locate corn tassel for corn detasseling machine. The corn tassel identification and location method was studied based on image processing and automated technology guidance information was provided for the actual production of corn emasculation operation. The system is the application of image processing to recognize and locate corn tassel for corn detasseling machine. According to the color characteristic of corn tassel, image processing techniques was applied to identify corn tassel of the images under HSI color space and Image segmentation was applied to extract the part of corn tassel, the feature of corn tassel was analyzed and extracted. Firstly, a series of preprocessing procedures were done. Then, an image segmentation algorithm based on HSI color space was develop to extract corn tassel from background and region growing method was proposed to recognize the corn tassel. The results show that this method could be effective for extracting corn tassel parts from the collected picture and can be used for corn tassel location information; this result could provide theoretical basis guidance for corn intelligent detasseling machine.

Paper Details

Date Published: 15 November 2011
PDF: 7 pages
Proc. SPIE 8335, 2012 International Workshop on Image Processing and Optical Engineering, 83350J (15 November 2011); doi: 10.1117/12.917672
Show Author Affiliations
Wenbing Tang, China Agricultural Univ. (China)
Yane Zhang, China Agricultural Univ. (China)
Dongxing Zhang, China Agricultural Univ. (China)
Wei Yang, China Agricultural Univ. (China)
Minzan Li, China Agricultural Univ. (China)


Published in SPIE Proceedings Vol. 8335:
2012 International Workshop on Image Processing and Optical Engineering
Hai Guo; Qun Ding, Editor(s)

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